Abstract for arandjelovic_AFG06

A NEW LOOK AT FILTERING TECHNIQUES FOR ILLUMINATION INVARIANCE IN
AUTOMATIC FACE RECOGNITION.

O. Arandjelović and R. Cipolla

2006

Illumination invariance remains the most researched, yet the most
challenging aspect of automatic face recognition. In this paper we
propose a novel, general recognition framework for efficient matching of
individual face images, sets or sequences. The framework is based on
simple image processing filters that compete with unprocessed greyscale
input to yield a single matching score between individuals. It is shown
how the discrepancy between illumination conditions between novel input
and the training data set can be estimated and used to weigh the
contribution of two competing representations. We describe an extensive
empirical evaluation of the proposed method on 171 individuals and over
1300 video sequences with extreme illumination, pose and head motion
variation. On this challenging data set our algorithm consistently
demonstrated a dramatic performance improvement over traditional
filtering approaches. We demonstrate a reduction of 50-75% in
recognition error rates, the best performing method-filter combination
correctly recognizing 96% of the individuals.

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